Mentoring strategies in a project-based learning environment: A focus on self-regulation
Notice bibliographique
Résumé
The main purpose of this Action Research investigation was to better understand how post-secondary faculty mentor self-regulatory behaviours in a project-based learning environment (PjBL). The secondary purpose was to understand how the Action Research process supported faculty in their mentoring. Lastly, understanding learner perceptions of being mentored and how the faculty’s mentoring of specific self-regulatory behaviors would align with the expectations of the video game industry, would provide a cross-section of intrigue into the investigation. The research context was the Master of Digital Media Program in Vancouver, Canada. The MDM Program specializes in providing learners, organized in project teams, the opportunity to work on real-world digital media projects. Three faculty mentors and three student teams participated in this study; each team was tasked with co-constructing video-game prototypes for three game companies over a four-month period. Pre-research interviews with established members of the video game industry in Vancouver were conducted in order to determine what qualities and skills they looked for when hiring new recruits. Data from these interviews revealed characteristics of self-regulation, such as self-motivation, ‘ownership’, the ability for recruits to manage their own learning, and self-reliance as being of primary importance. A pilot study was then undertaken to operationalize self-regulation as reflected in the mentoring practices of one MDM faculty member and assess the effectiveness of the planned data collection procedures. The primary investigation consisted of video recording the mentoring sessions of three faculty and three student teams, a total of 18 students. Video recorded mentoring sessions were observed and discussed by the researcher and each faculty member in a one-on-one interview setting. Final faculty and student interviews were conducted. Data from pre-research interviews, the stimulated recall sessions, and final interviews were analyzed and triangulated. Triangulation of learner interviews revealed that mentors supported self-regulatory behaviors using a variety of strategies, which are described in detail. Triangulation of pre-research interviews revealed that mentors were supporting learners in their development of specific characteristics expected of new recruits transitioning into the video game industry.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,011 | 0,018 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,004 |
| Communication savante | 0,005 | 0,002 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».